Propuesta comunicativa 2

With all “good” WIMP-search data series identified, we place cuts on the reconstruction quality of individual events in the eligible data series. This is done for calibration data as well.

6.4.1

Event reconstruction

The RQQSOFchisq, which is theχ2_{goodness-of-fit parameter from the charge optimal filter, is used}

to assess charge reconstruction quality on an event-by-event basis. This is done primarily to reject “pileups”, the occurrence of more than one particle hit in a single trace length of_∼1640µs. Such traces cannot be used to correctly estimate energy or timing. Pileups have large optimal filter χ2

values and can be removed by setting a cut on this parameter, as a function of energy. Intuitively, an energy dependence is not expected but is seen as shown in Figure 6.6 for a couple of reasons [71]. First, the template is not perfect — it is obtained by averaging several pulses, and at large energies,

the noise in the template makes the goodness-of-fit worse. Second, the charge pulse start time is determined only to the nearest time bin, which is 0.8µs. Sub-bin interpolation has been shown to reduce the energy dependence of the χ2 _{value, but was not implemented in BatRoot in time for}

Runs 125–128.

Figure 6.6: QSOFchisq vs. summed charge energy for133_{Ba-calibration data in T1Z2 in Run 125.}

The energy bin centers used for fitting are marked with crosses. The cut is marked by the line through the crosses. Data points under the line, marked in blue, are accepted and red ones, above the line, are rejected. Courtesy: Sebastian Arrenberg.

The cut cChiSq c58was defined in the following way. Theχ2_{distributions for each detector in}

each run were binned into four energy intervals. Then theχ2_{values in each bin were fit to a gaussian.}

The 3.5σ χ2 _{values from each of the bins were fit to a quadratic to provide the energy-dependent}

cut [155]. The cut is shown in Figure 6.6 for detector T1Z2 in Run 125.

Note that the primary WIMP-search analysis for Runs 125–128 does not employ a phonon reconstruction cut based on the phonon optimal filter goodness-of-fit parameter. This is because of inherent phonon-pulse-shape variation, leading to large variation in χ2 _{values. In the case of the}

charge optimal filter, the χ2 parameter can be used for a reconstruction quality cut because the charge pulse is truly expected to have a known shape set by the electronics. However, I note that analyses using the time-domain-fitting algorithms PipeFit and WedgeFit, described in Section 6.2.6 of [104] use goodness-of-fit cutscPFGoodFit c58andcWFGoodFit c58[156].

6.4.2

Phonon pre-pulse baseline

The second line of defense against pileup events is a cut on the standard deviation of pre-pulse baseline of the phonon traces. This helps to identify traces that may contain residual long phonon tails of events preceding the global trigger. Such traces need to be discarded for the same reason as

before — ambiguity in determining energy and timing information. Note that this pathology is not tackled by the charge goodness-of-fit cut because ionization pulses have much shorter falltimes than phonon pulses.

The cut cPstd c58 rejects phonon-tail pileup events. It was made by fitting a gaussian to the distribution of the standard deviation of the first _∼400µs (stored as RQ P*std) of all traces of a data series and then rejecting 5σoutliers on a series-by-series basis [157, 158]. In past analyses, the fits were made to the baseline standard deviation for the entire run, but the new technique prevents entire data series from being penalized by shifts in noise, and hence baseline standard deviation, over long time periods. Figure 6.7 showsP*stddistributions for detector T1Z2 and the final cut for Run 125. The efficiency of this cut is∼99% for most detectors and is accounted for detector-by-detector and run-by-run in the final efficiency calculation.

Figure 6.7: Baseline standard deviation vs. time for T1Z2 in Run 125. Blue data points represent events accepted bycPstd c58, and the cyan lines indicate the cut. Red data points represent events removed by the cut. Courtesy: David Moore.

6.4.3

Charge pre-pulse baseline

The charge pre-pulse baseline cut, cQstd c58, is similar in implementation to the phonon pre- pulse baseline cut. However, the purpose of this cut is to reject events with high noise caused by microphonic pickup from cryocooler mechanical vibrations. The cryocooler, attached at the e- stem of the experiment, undergoes mechanical compression cycles with frequency 0.8 Hz, ringing

the system at all frequencies with every cycle. The phonon channels and most charge channels are immune to this issue, whereas the fiducial charge channels of detectors T1Z4, T3Z2, and T3Z5 and the outer charge channels of T1Z4, T2Z1, T2Z3, T2Z5, T3Z2, and T3Z5 are susceptible. Figure 6.8 shows noise spectra for T1Z4 during Runs 123–124 with and without cryocooler operation. The frequency and amplitude of cryocooler cycles are sufficiently varied for a blanket livetime cut at known intervals. Thus, the charge pre-pulse baseline, an indicator of cryocooler-induced noise, is the best identifier to tag and cut events affected by cryocooler cycling.

103 104 105 106 10−8 10−7 10−6 10−5 Frequency [Hz] Noise r.m.s. amplitude [V/ √ Hz] T1Z4 Qinner Cryocooler OFF: 0.400 keV Cryocooler ON: 0.493 keV (+23.1%)

Figure 6.8: Noise power spectra for T1Z4 in Runs 123–124 with (red) and without (black) cryocooler operation. The caption indicates the r.ms. resolution in the two cases. Courtesy: Jeff Filippini.

Similar to cPstd c58, gaussians are fitted to the distribution of Q*std, the charge pre-pulse baseline for all traces of a data series, and then traces with Q*std >4σare removed on a series- by-series basis [157, 158]. Once again, the series variation of the threshold allows noise to drift over long time scales during a run, without penalizing entire series. Series with unusually high noise were already removed using the cuts described in Section 6.3.4. For detectors T2Z3 (fiducial), T3Z5 (fiducial and outer) and T4Z5 (fiducial), the thresholds were adjusted to 3σ,3σ, and 2.5σ, respectively, to account for extended periods of high-frequency noise, which artificially inflate the Q*stddistribution. The efficiency of this cut is∼99% for most detectors is accounted for detector- by-detector and run-by-run in the final efficiency calculation.

6.4.4

Phonon start time

A different pileup pathology is that of “cross-detector” pileup in high-event-rate calibration data, when a particle hit in a detector other than the triggering detector appears outside the optimal-

filter-search window. When the DAQ receives a global trigger, traces from all detectors2_{are recorded}

within_∼[₋400,+1200]µs of the global trigger. During first-tier data processing, the reconstruction algorithms search for an ionization (phonon) pulse in all recorded traces only inside a window of [₋100,+10]µs ([₋50,+200]µs) around the global trigger. An unrelated event on a non-triggering detector may not fall in the search window of the triggering event. The “walked” phonon timing and optimal-filter phonon energy for such a non-triggering event is typically reconstructed correctly because of a relatively large search window. However, the optimal filter ionization energy and start time might be misreconstructed, leading to anomalously long phonon delays and lower yields. Such events can be immune to other event reconstruction cuts. Figure 6.9 shows an example of an event where the charge pulse does not lie in the search window defined by the triggering detector.

Figure 6.9: Charge and phonon traces of an event in detector T1Z3 where the trigger was issued by another detector. The charge pulse lies outside the search window. The true charge amplitude is 4.6 keV, but is reconstructed as 1.6 keV from the noise in the search window. Also the charge start time is assigned to be 416.8µs. The reconstructed charge fit has a sufficiently lowQSOFchisq to pass the event reconstruction cut. Courtesy: Jeff Filippini.

The cutcGoodPStartTimerejects events that do not lie in the overlap of the charge and phonon- pulse-search windows, i.e., [−50,+10]µs [159, 160]. With few exceptions, the efficiency of this cut is 100%. Note that increasing the charge-pulse-search window in first-tier processing would be computationally expensive, and enforcing the overlap criterion of this cut during reconstruction would produce erroneous walk algorithm times. Thus far, the best solution seems to be enforcing the requirement after data processing. Also, this is not a problem for WIMP-search data with low event rates.

6.4.5

Phonon manifold distance

As explained in Section 4.4.3, the distance of all events to the lookup table averaging bin used for their correction is recorded. In particular, two distances are measured by CorrTools during phonon-pulse-shape correction and recorded by PipeCalib as RRQs during data processing.

1. Distance to position manifold (pchisq m rtft):d=

q

∆xppart2+ ∆yppart2+∆xdel

Ldel 2

+∆ydel

Ldel 2

2. Distance to timing manifold (pchisq t rtft): d=p∆pminrt2+ ∆pdel2

Note that these two distance measures are not used to determine the choice of nearest neighbors in the averaging bin. That is done by Equation 4.9, as described in Chapter 4. These two distance measures are used as a check on the correction quality because we found timing outliers to be correlated with large distances from their lookup table bins. Thus, we devised a cut cGoodRTFTManifold c58 to reject the outlier tail in the sum of these two parameters with 97% efficiency for nuclear recoils [129]. The analog cut for PipeFit timing quantities is called cGoodPFManifold c58, and uses distance analogs for PipeFit quantities.